The diagnosis and treatment of patients with brain tumors and other diseases is often critically dependent on functional neuroimaging (e.g. fMRI) to identify healthy brain tissue that must be avoided during invasive surgery or radiation treatment. But, conventional fMRI often fails (up to 30 percent) or cannot be used with patients who are unable to adequately perform the required behavioral tasks. Resting-state, functional connectivity MRI (fcMRI) provides a potential alternative to task-based fMRI for mapping the brain. fcMRI was first developed at the Medical College of Wisconsin by Biswal and colleagues1 who observed that fluctuations in fMRI signals during behavioral rest are temporally correlated within functionally related cortical networks such as the motor system but not between functionally unrelated networks. Practically, this means that approximately 20 functionally distinct brain systems can be mapped simultaneously with a single 5-10 minute sample of fMRI data obtained while the patient does nothing but rest quietly in the MRI scanner. This approach has exceptional practical utility for clinical applications such as brain mapping prior to brain cancer surgery. Compared to more conventional task-based fMRI, fcMRI is faster, simpler, and less behaviorally demanding since it does not depend on accurate task performance. As a result, it can be used with patients who are anesthetized or too young, too old, too debilitated or too uncooperative to perform a challenging behavioral task. In addition, theoretical connectivity concepts provide potential indicators of brain dysfunction related to pathological changes in functional connectivity. Despite its potential clinical utility, fcMRI has not been optimized for clinical use, nor has its validity as an indicator of brain function been adequately characterized, especially in the presence of operable brain pathologies. Although there are significant initiatives to develop connectivity methods for basic research, far less is being done to promote its use for clinical applications. Indeed, at this juncture, clinically optimized tools for the acquisition, analysis and display of fcMRI data are not available. Thus, the overall goal of this multi-institutional project is to develop a suite of software tools for the routine clinical use of fcMRI and to validate their use with patients suffering from brain cancer, and other operable brain diseases. In this Phase I project, we will focus on developing a prototype system, installing it at suitable hospital sites, and testing it with a small sample of patients in order to demonstrae feasibility. This will lead to a more extensive Phase II project in which the system will be refine for eventual commercial release and tested with a wider range of patients to fully characterize the validity of fcMRI for specific clinical applications. It is anticipated that the successful completion of this project will provide a widely available, professional product, help remove current impediments to use of fcMRI clinically, promote its acceptance within the health care and insurance industries, and extend the benefits of advanced neuroimaging to the treatment of a much wider population of patients with brain disease.